Yes, now I notice that point. Thank you so much for your help, Andrea "Hooiveld, Guido" <guido.hooiveld at="" wur.nl=""> ha scritto: > Hi Andrea, > I have to admit that it has been a while since I actively used > Harshlight. However, AFAIK Harshligt detect both outlier probes. You > can have Harslight automatically correct these outlier probes by > having their (outlier) value replaced by either 'NA' or by the > median value for all arrays. > See '?Harshlight' for more details: "na.sub: If TRUE, the intensity > values of the input affyBatch that are affected by defects will be > changed in NA. If FALSE, the values will be substituted with the > median of the intensity values of the other chips." > > If you have a brief look at Figure 2 of this Harshlight paper > http://www.biomedcentral.com/1471-2105/6/294 you will see that a > representative image of all arrays is obtained by creating a 'median > image'. Each individual array is then compared to this median image, > and defects are identified by deviations to the median image using a > set of criteria (again see ?Harshlight for more details). > Thus, the number of arrays that is analysed together will (slightly) > affect the outcomes of Harshlight. If I were you I would analyse all > arrays from an experiment together (in your case all 40), have > Harshlight replace all outlier values by the median, and then > continue with normalizing using e.g. (GC)RMA. > > HTH, > Guido > > -----Original Message----- > From: andrea.grilli at ior.it [mailto:andrea.grilli at ior.it] > Sent: Wednesday, May 09, 2012 10:20 > To: Hooiveld, Guido > Cc: bioconductor at r-project.org > Subject: Re: [BioC] outlier probes detection > > Hi Guido, > thank you for your reply. > I checked the package Harshlight you suggested. Although it detects > outlier arrays (and not outlier probes) it works well for the case, > because it gives a percentage of the defects and that's better than > a simple visual evaluation. > I have one question about the package evaluation of these defects. > Because of the intense calculation, I tried either splitting the > case study in two groups (20 and 20 arrays) and later on with the 40 > chips all together: according to the package output, one array > should be excluded only in the second case. Is there some sort of > evaluation of the defects depending also on the set of arrays a chip > is analyzed with? I flipped through the concerning paper but I > didn't find any information about that.. > > I also checked the solution proposed by Okko (thank you for your > suggestion), but because it's a stronger approach I'll need more > time to evaluate it. > > Andrea > > > "Hooiveld, Guido" <guido.hooiveld at="" wur.nl=""> ha scritto: > >> Hi Andrea, >> >> If the affected area is relatively small (less than 5-10% of total >> area) we usually ignore these scratches/bubbles (because each probeset >> is comprised of multiple probes, and the robust summarization methods >> usually used within RMA (median polish or >> M-estimator) are able to handle these outliers pretty well). >> Alternatively, the package 'Harshlight' offers options to correct for >> various types of artefacts. >> http://www.bioconductor.org/packages/2.10/bioc/html/Harshlight.html >> >> Regards, >> Guido >> >> --------------------------------------------------------- >> Guido Hooiveld, PhD >> Nutrition, Metabolism & Genomics Group Division of Human Nutrition >> Wageningen University Biotechnion, Bomenweg 2 >> NL-6703 HD Wageningen >> the Netherlands >> tel: (+)31 317 485788 >> fax: (+)31 317 483342 >> email: guido.hooiveld at wur.nl >> internet: http://nutrigene.4t.com >> http://scholar.google.com/citations?user=qFHaMnoAAAAJ >> http://www.researcherid.com/rid/F-4912-2010 >> >> >> -----Original Message----- >> From: bioconductor-bounces at r-project.org >> [mailto:bioconductor-bounces at r-project.org] On Behalf Of >> andrea.grilli at ior.it >> Sent: Tuesday, May 08, 2012 12:15 >> To: bioconductor at r-project.org >> Subject: [BioC] outlier probes detection >> >> >> Dear all, >> I'm performing an analysis on HGU133plus2 arrays with 40 samples; >> looking at their surface with "affyPLM" package, I've seen a couple of >> arrays with small scratches and one more with a small bubble. >> Because I don't want to exclude these arrays (according to Murphys' >> law 2 on 3 belong to the class with less samples), I want to detect >> those probes and to exclude them. >> I was thinking in some outlier detection method, but because I'm new >> to this problem I don't know if this is the right method and which >> packages can be appropriate (did some research but I've no clear >> idea). >> Any help is really appreciated, >> andrea >> >> >> >> >> Dr. Andrea Grilli >> andrea.grilli at ior.it >> phone 051/63.66.756 >> >> Laboratory of Experimental Oncology, >> Development of Biomolecular Therapies unit, Rizzoli Orthopaedic >> Institute Codivilla Putti Research Center via di Barbiano 1/10 >> 40136 - Bologna - Italy >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor Dr. Andrea Grilli andrea.grilli at ior.it phone 051/63.66.756 Laboratory of Experimental Oncology, Development of Biomolecular Therapies unit, Rizzoli Orthopaedic Institute Codivilla Putti Research Center via di Barbiano 1/10 40136 - Bologna - Italy